By Benoit Gaudou, Jaime Simao Sichman

ISBN-10: 3319314467

ISBN-13: 9783319314464

ISBN-10: 3319314475

ISBN-13: 9783319314471

This booklet constitutes the completely refereed post-conference lawsuits of the sixteenth foreign Workshop on Multi-Agent-Based Simulation, MABS 2015, held in Istanbul, Turkey, in may well 2015. The workshop was once held at the side of the 14th overseas convention on independent brokers and Multi-agent platforms, AAMAS 2015.

The 12 revised complete papers incorporated during this quantity ware rigorously chosen from 22 submissions. The papers specialise in the effect of social sciences and multi-agent structures, with a powerful application/empirical vein, and its emphasis is under pressure on exploratory agent dependent simulation as a principled approach of venture medical study within the social sciences and utilizing social theories as an suggestion to new frameworks and advancements in multi-agent systems.

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Additional info for Multi-Agent Based Simulation XVI: International Workshop, MABS 2015, Istanbul, Turkey, May 5, 2015, Revised Selected Papers

Example text

Then we rewire some of the nodes. 2 to 1. Results are summarized in Figs. 7 and 8. In the case of regular networks, we can observe that the MaxI value increases and the TimeofMaxI and Duration decrease when the number of edges increases. 30 A. Banos et al. Fig. 8. 8, 1} It is due to the fact that it is easier to infect other nodes when it is easier to access them via the network (which is allowed by increasing the number of edges). In the case of the small-world networks, we have similar observation when we increase the rewiring probability.

Marshalling the data structures between C++ and Haskell) and housekeeping, in particular garbage collection. This may represent a bottleneck for large populations which we aim to address as part of the future work. – MC2 MABS also scales linearly with the population size in the case of universally quantified formulae. However, housekeeping (particularly garbage collection) becomes a serious overhead as the number of agents grows. g. by employing strictness in some of the operations. Profiling memory consumption for a lazy language like Haskell can be difficult.

Fig. 6. Influence of the area size on the indicators MaxI, TimeofMaxI and Duration It could be interesting to investigate the second explanation. A way to do could be to replace the ODE model by a Gillespie algorithm that is dedicated to small population (everything else in the model remaining unchanged). 4 Impact of the Network In order to study the impact of the network topology on results, we consider the same model initialized with various networks. In every case, we consider a network with 100 nodes (cities).

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Multi-Agent Based Simulation XVI: International Workshop, MABS 2015, Istanbul, Turkey, May 5, 2015, Revised Selected Papers by Benoit Gaudou, Jaime Simao Sichman

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